REPLICATION PACKAGE FOR “REVISITING THE ORIGINS OF BUSINESS CYCLES WITH THE SIZE-VARIANCE RELATIONSHIP“ (YEH, RESTAT 2023)

*******************
*** 1. OVERVIEW ***
*******************

- The programs/codes in this replication package allows the user to generate all figures and tables in “Revisiting the Origins of Business Cycles with the Size-variance Relationship“ (Yeh, REStat 2023). 
	- All tables/figures can be replicated using Stata.
	- The exceptions are:
		- Table II (Mathematica)
		- Table A4 and Table A5 in Appendix B (Stata/Matlab)
	
- This paper uses confidential microdata from the U.S. Census Bureau.
	- This document provides a brief description and details on how to access this data.
	- Once your application for data from the Census Bureau is approved, you can use the replication files from section 7 to replicate this paper.

******************************************************
*** 2. DATA AVAILABILITY AND PROVENANCE STATEMENTS ***
******************************************************

- To replicate the results in the paper, you will need to access confidential firm-year level data from the Census Bureau through a Federal Statistical Research Data Center (FSRDC).
	- These data are constructed from the Longitudinal Business Database files.

- Interested researchers can apply for confidential data from the Census Bureau by submitting a proposal. 
	- Details on how to write and submit a proposal can be found here:
	  https://www.census.gov/programs-surveys/ces/data/restricted-use-data/apply-for-access.html
	- While the Census Bureau does not provide exact timelines, users should expect that it may take 6-18 months before their proposal is approved.
		- After your project is approved, you will also need to obtain Special Sworn Status (SSS) which may take an additional few months (but can be applied for concurrently).
	- Access requires that the user is affiliated with an U.S. institution that provides physical access to a FSRDC.
		- Furthermore, a minimal residency requirement in the U.S. of 3 years must be satisfied.

- In order to replicate the paper, your approved project should contain, at least, the following data sets:
	- Longitudinal Business Database (LBD), 1976 - 2011

- Once access is granted, data files from the LBD (in .sas format) can be located from the standard data directory at the Census server.

**********************************
*** 3. SUMMARY OF AVAILABILITY ***
**********************************

- The administrative data from the Census Bureau cannot be made publicly available.

**************************************
*** 4. DETAILS ON EACH DATA SOURCE ***
**************************************

- Longitudinal Business Database (LBD)
	- The LBD is an annual data set that contains the near-universe of employer establishments; details can be found in Jarmin and Miranda (2002) and Chow et al. (2021).
	- This project uses the 2016 vintage of the LBD and commenced when the “revised LBD” as described in Chow et al. (2021) was not yet available.

- Once access is granted, raw data files from the LBD (in .sas format) can be located from the standard data directory on the Census server.
	- These files can be pulled with a SAS program or the “import sas” command in Stata.

*************************************
*** 5. COMPUTATIONAL REQUIREMENTS ***
*************************************

- All results can be replicated with Stata (version 16 or higher), Mathematica (version 12 or higher) and Matlab (version 9 or higher).

***************************************************************
*** 6. DESCRIPTION OF PROGRAMS/CODES IN REPLICATION PACKAGE ***
***************************************************************

- Stata
	- “0_data_construction.do” constructs several data sets that are required to replicate the results in the main text and Appendix A
	- “1_main_results.do” generates the results in Table I and Figure 1
	- “2_appendix_A.do” generates all of the results in Appendix A (Tables A1, A2 and A3)
- Mathematica
	- “simulation_structural_compiled_final.nb” generates the results of Table II
- Stata/Matlab
	- The folder “3_appendix_B” contains Stata .do and Matlab .m files to generate the results in Appendix B (Tables A4 and A5)
		- Note that this code was originally written by Di Giovanni, Levchenko and Mejean (Econometrica, 2014); credit for this part of the code should go to them. 
	- To replicate the results in Appendix B, the order of running the files should be as follows:
		1. “dGLM_0_datapreparation.do” (Stata)
		2. “dGLM_1_microestimation_all.do” (Stata)
			- This .do file invokes the following .do files:
				- “dGLM_2_growth_regs.do” (State)
				- “dGLM_4_threesteps_growth_regs.do” (Stata)
				- “dGLM_9_matlab_prep.do” (Stata)
		3. “dGLM_1_import_all.m” (Matlab)
		4. “dGLM_2_master_variance_all_ca.m” (Matlab)
			- This .m file invokes the following .m files:
				- “ag_growth.m”
				- “var_growth.m”
				- “var_only_growth.m”
				- “herfindahl.m”
				- “w_matrix.m”

*************************************
*** 7. LIST OF TABLES AND FIGURES ***
*************************************

*** MAIN TEXT **
* TABLES AND FIGURES *
- Table I: Results for baseline size-variance regressions
- Figure 1: Results for non-parametric size-variance regressions
- Table II: Simulation results

*** APPENDIX ***
* TABLES AND FIGURES *
- Table A1: Robustness - Size-variance relationship (alternative measures for growth and volatility)
- Table A2: Robustness - Size-variance relationship (higher-order polynomial regressions)
- Table A3: Robustness - Size-variance relationship (regressions with large firms only)
- Table A4: Robustness - Importance of size-variance relationship for granular channel (main components)
- Table A5: Robustness - Importance of size-variance relationship for granular channel (Idiosyncratic components)

*********************
*** 8. REFERENCES ***
*********************

- Chow, M., Fort, T.C., Goetz, C., Goldschlag, N., Lawrence, J. Perlman, E.R., Stinson, M. and K.T. White (2021), “Redesigning the Longitudinal Business Database”, Census CES Working Paper Series, CES-21-08.
- Di Giovanni, J., Levchenko, A. and I. Mejean (2014), “Firms, Destinations, and Aggregate Fluctuations”, Econometrica, 82(4), p. 1303-1340.
- Jarmin, R.S. and J. Miranda (2002), “The Longitudinal Business Database”, Census CES Working Paper Series, CES-02-17.
- Yeh, C. (2023), “Revisiting the Origins of Business Cycles with the Size-variance Relationship”, Review of Economics and Statistics.
